@inproceedings{schreiber-etal-2018-nlp,
    title = "{NLP} Lean Programming Framework: Developing {NLP} Applications More Effectively",
    author = {Schreiber, Marc  and
      Kraft, Bodo  and
      Z{\"u}ndorf, Albert},
    editor = "Liu, Yang  and
      Paek, Tim  and
      Patwardhan, Manasi",
    booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Demonstrations",
    month = jun,
    year = "2018",
    address = "New Orleans, Louisiana",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/N18-5001",
    doi = "10.18653/v1/N18-5001",
    pages = "1--5",
    abstract = "This paper presents NLP Lean Programming framework (NLPf), a new framework for creating custom Natural Language Processing (NLP) models and pipelines by utilizing common software development build systems. This approach allows developers to train and integrate domain-specific NLP pipelines into their applications seamlessly. Additionally, NLPf provides an annotation tool which improves the annotation process significantly by providing a well-designed GUI and sophisticated way of using input devices. Due to NLPf{'}s properties developers and domain experts are able to build domain-specific NLP application more effectively. Project page: \url{https://gitlab.com/schrieveslaach/NLPf} Video Tutorial: \url{https://www.youtube.com/watch?v=44UJspVebTA} (Demonstration starts at 11:40 min) This paper is related to: - Interfaces and resources to support linguistic annotation - Software architectures and reusable components - Software tools for evaluation or error analysis",
}